CyberTraining: Implementation: Medium: Computational Materials Science Summer School - Fostering Accelerated Scientific Techniques (CMS3-FAST)

网络培训：实施：媒介：计算材料科学暑期学校 - 促进加速科学技术 (CMS3-FAST)

• 批准号: 2321005
• 负责人: Ankit Srivastava
• 金额: $ 98.32万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321005&HistoricalAwards=false
• 关键词: CyberTraining; Implementation; Medium; Computational; Materials

Advancing Materials Science and Engineering (MSE) is not only important but critical for discovering innovative and sustainable solutions to some of the most pressing challenges facing our society today. The integration of Computational Materials Science (CMS) and Machine Learning (ML)/Artificial Intelligence (AI) techniques, along with Accelerated High-Performance Computing (AHPC) achieved using modern hardware accelerators, can provide a powerful platform for researchers to accelerate advancements in MSE. However, the rapid advancement of these fields has also created a knowledge gap in the workforce, with a shortage of professionals who are simultaneously trained in all three areas: CMS, ML/AI, and AHPC. This project is a beyond-state-of-the-art workforce development program that will integrate CMS, ML/AI techniques, and AHPC into one comprehensive education and hands-on training program to drive transformative fundamental research in MSE. The project will utilize immersive visualization through Virtual and Augmented Reality (VR/AR) tools and AI-based natural language generation tools to provide a tailored environment for participants with different backgrounds and learning styles. The education and hands-on training components of this project are both hybrid and expansive, allowing for large-scale workforce development. In addition, the project will develop studio-based curricula that integrate CMS, ML/AI techniques, and AHPC at various levels of complexity for both undergraduate and graduate students. It will establish partnerships with national laboratories, other academic institutions, and a large network of CMS and CI professionals and contributors. These collaborations will promote a collective impact on training-based workforce development and advancements in MSE. The program also aims to introduce immersive visualization and materials informatics in CMS to K-12 students to promote and encourage their interest in pursuing higher education in related fields. The specific objectives of this project are to: (i) Integrate CMS, ML/AI techniques, and AHPC into one comprehensive education and hands-on training program. (ii) Leverage immersive visualization through VR/AR tools and AI-based natural language generation tools to provide a tailored environment to participants with different backgrounds and learning styles. (iii) Rigorously test and enhance the scaling of the education and hands-on training components, while also broadening access to enable large-scale and unrestricted workforce development. (iv) Develop studio-based curricula that integrate CMS, ML/AI techniques, and AHPC at various levels of complexity for both undergraduate and graduate students. (v) Expand the current network of CI professionals and contributors to establish a powerful platform that accelerates advancements in MSE through continuous training and development. By achieving these objectives, this project will create a new generation of highly skilled CI users, equipped with cutting-edge tools and techniques to drive innovation in MSE.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Civil, Mechanical and Manufacturing Innovation within the Directorate for Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

推进材料科学与工程（MSE）不仅重要，而且对于发现当今社会面临的一些最紧迫的挑战而言，发现创新和可持续的解决方案至关重要。计算材料科学（CMS）与机器学习（ML）/人工智能（AI）技术的整合以及使用现代硬件加速器实现的加速高性能计算（AHPC）的整合，可以为研究人员提供一个强大的平台，以使MSE加速进步。但是，这些领域的迅速发展也在劳动力中造成了知识差距，而在所有三个领域都接受过同时培训的专业人员：CMS，ML/AI和AHPC。该项目是一项超越状态的劳动力发展计划，它将将CMS，ML/AI技术和AHPC整合到一个全面的教育和动手培训计划中，以推动MSE的变革性基础研究。该项目将通过虚拟和增强现实（VR/AR）工具和基于AI的自然语言生成工具利用沉浸式可视化，为具有不同背景和学习风格的参与者提供量身定制的环境。该项目的教育和动手培训组成部分是混合动力和广泛的，可以进行大规模的劳动力发展。此外，该项目还将开发基于工作室的课程，该课程将本科生和研究生的CMS，ML/AI技术和AHPC集成到各种复杂性。它将与国家实验室，其他学术机构以及CM和CI专业人士和贡献者建立合作伙伴关系。这些合作将促进对基于培训的劳动力发展和MSE进步的集体影响。该计划还旨在将CMS中的沉浸式可视化和材料信息学引入K-12学生，以促进和鼓励他们对在相关领域进行高等教育的兴趣。该项目的具体目标是：（i）将CMS，ML/AI技术和AHPC整合到一个全面的教育和动手培训计划中。 （ii）通过VR/AR工具和基于AI的自然语言生成工具利用沉浸式可视化，为具有不同背景和学习风格的参与者提供量身定制的环境。 （iii）严格测试和增强教育和动手培训组件的缩放，同时还扩大了实现大规模和不受限制的劳动力发展的机会。 （iv）开发基于工作室的课程，该课程将本科和研究生的CMS，ML/AI技术和AHPC集成到各种复杂性的水平。 （v）扩展当前的CI专业人员和贡献者网络，以建立一个强大的平台，通过持续培训和开发加速MSE的进步。通过实现这些目标，该项目将创建新一代高技能的CI用户，配备了尖端的工具和技术来推动MSE的创新。这一奖项获得了高级网络基础设施办公室的奖项，共同支持了公民，机械和制造部的工程学奖，该奖项是通过Interginient of Engineering of Interentions的授权，并反映了DEEM的宣称。优点和更广泛的影响审查标准。